

*** Basic Confidence
melogit state_conf c.COVIDCOVI_2020 b1.party3 i.votingmethod i.race4 female i.educ3 age date firm_num trifecta20 [pw=norm_state_weight] if sample == 1  || state_fips:


*** Party Interaction Confidence
melogit state_conf c.COVIDCOVI_2020##b1.party3 i.votingmethod i.race4 female i.educ3 age date firm_num trifecta20 [pw=norm_state_weight] if sample == 1  || state_fips:

*** Vote Interaction 
melogit state_conf c.COVIDCOVI_2020##i.pres_2 b1.party3 i.votingmethod i.race4 female i.educ3 age date firm_num trifecta20 if sample == 1  [pw=norm_state_weight] || state_fips:

melogit state_conf c.COVIDCOVI_2020##i.pres_2 b1.party3 i.votingmethod i.race4 female i.educ3 age date firm_num trifecta20 if sample == 1  & party3 == 1 | sample == 1  & party3 == 3 [pw=norm_state_weight] || state_fips:

melogit state_conf c.COVIDCOVI_2020##i.pres_2 b1.party3 i.votingmethod i.race4 female i.educ3 age date firm_num trifecta20 if sample == 1  & party3 == 2 [pw=norm_state_weight] || state_fips:

*** National Confidence
melogit national_conf c.COVIDCOVI_2020##b1.party3 i.votingmethod i.race4 female i.educ3 age date firm_num trifecta20 [pw=norm_state_weight] if sample == 1  || state_fips: 

*** Personal Confidence
melogit personal_conf c.COVIDCOVI_2020##b1.party3 i.votingmethod i.race4 female i.educ3 age date firm_num trifecta20 [pw=norm_state_weight] if sample == 1  || state_fips:

*** Local Confidence
melogit county_conf c.COVIDCOVI_2020##b1.party3 i.votingmethod i.race4 female i.educ3 age date firm_num trifecta20 [pw=norm_state_weight] if sample == 1  || state_fips:  

***************
*** Figures ***
***************

*** Rugs
hist COVIDCOVI_2020
gen where1 = .18
gen pipe1 = "|"

hist COVIDCOVI_2020
gen where2 = .58
gen pipe2 = "|"

*** No interaction *** 
melogit state_conf c.COVIDCOVI_2020 b1.party3 i.votingmethod i.race4 female i.educ3 age date firm_num trifecta20 [pw=norm_state_weight] if sample == 1  || state_fips:
su COVIDCOVI_2020, d
local min = r(min)
local max = r(max)
margins, at(COVIDCOVI_2020=(`r(min)' (0.1) `r(max)')) 
marginsplot, recastci(rarea) ciopts(color(gs10%40) lcolor(white)) yti("Predicted Probability of Confidence", size(small)) xti("Cost of Voting", size(small)) title("D. 2020 (Integrity of Voting)", size(small) nospan) plot1opts(color(black) msize(small) msymbol(smcircle) lpattern(soild)) ylab(.6 (.1) 1, nogrid tlcolor(black) nogextend labs(small)) ylab(.6 (.1) 1, nogrid tlcolor(black)) xscale( lc(black)) yscale( lc(black)) addplot(scatter where2 COVIDCOVI_2020, ms(none) mlabel(pipe2) mlabpos(0) xlab(-2.9 (.4) 1.6, nogrid tlcolor(black) labs(small)) ylab(.6 (.1) 1, nogrid tlcolor(black)) xscale( lc(black))) legend(off) scheme(s1mono) name(me20n)

*** Interaction *** 
melogit state_conf c.COVIDCOVI_2020##b1.party3 i.votingmethod i.race4 female i.educ3 age date firm_num trifecta20 [pw=norm_state_weight] if sample == 1  || state_fips:
su COVIDCOVI_2020, d
local min = r(min)
local max = r(max)
margins, at(COVIDCOVI_2020=(`r(min)' (0.1) `r(max)') party3=(1 3)) 
marginsplot, recastci(rarea) ciopts(color(gs10%40) lcolor(white)) yti("Predicted Probability of Confidence", size(small)) xti("Cost of Voting", size(small)) title("D. 2020 (Integrity of Voting)", size(small) nospan) plot1opts(color(blue*1.2) msize(small) msymbol(smcircle) lpattern(soild)) plot2opts(color(red*1.2) msize(small) msymbol(smcircle) lpattern(soild)) ylab(.2 (.1) 1, nogrid tlcolor(black) nogextend labs(small)) ylab(.2 (.1) 1, nogrid tlcolor(black)) xscale( lc(black)) yscale( lc(black)) addplot(scatter where1 COVIDCOVI_2020, ms(none) mlabel(pipe1) mlabpos(0) xlab(-2.9 (.4) 1.6, nogrid tlcolor(black) labs(small)) ylab(.2 (.1) 1, nogrid tlcolor(black)) legend(order(3 "Democrats" 4 "Republicans") size(small) region(lcolor(white)) nospan)) legend(col(3) position(6)) scheme(s1mono) name(i20n)

*** Vote Choice ***
melogit state_conf c.COVIDCOVI_2020##i.pres_2 b1.party3 i.votingmethod i.race4 female i.educ3 age date firm_num trifecta20 if sample == 1  [pw=norm_state_weight] || state_fips: 
su COVIDCOVI_2020, d
local min = r(min)
local max = r(max)
margins, at(COVIDCOVI_2020=(`r(min)' (0.1) `r(max)') pres_2=(0 1)) 
marginsplot, recastci(rarea) ciopts(color(gs10%40) lcolor(white)) yti("Predicted Probability of Confidence", size(small)) xti("Cost of Voting", size(small)) title("D. 2020 (All)", size(small) nospan) plot1opts(color(blue*1.2) msize(small) msymbol(smcircle) lpattern(soild)) plot2opts(color(red*1.2) msize(small) msymbol(smcircle) lpattern(soild)) ylab(.2 (.1) 1, nogrid tlcolor(black) nogextend labs(small)) ylab(.2 (.1) 1, nogrid tlcolor(black)) xscale( lc(black)) yscale( lc(black)) addplot(scatter where1 COVIDCOVI_2020, ms(none) mlabel(pipe1) mlabpos(0) xlab(-2.9 (.4) 1.6, nogrid tlcolor(black) labs(small)) ylab(.2 (.1) 1, nogrid tlcolor(black)) legend(order(3 "Voted Democratic" 4 "Voted Republican") size(small) region(lcolor(white)) nospan)) legend(col(3) position(6)) scheme(s1mono) name(vc20_1)

melogit state_conf c.COVIDCOVI_2020##i.pres_2 b1.party3 i.votingmethod i.race4 female i.educ3 age date firm_num trifecta20 if sample == 1  & party3 == 1 | party3 == 3 [pw=norm_state_weight] || state_fips: 
su COVIDCOVI_2020, d
local min = r(min)
local max = r(max)
margins, at(COVIDCOVI_2020=(`r(min)' (0.1) `r(max)') pres_2=(0 1)) 
marginsplot, recastci(rarea) ciopts(color(gs10%40) lcolor(white)) yti("Predicted Probability of Confidence", size(small)) xti("Cost of Voting", size(small)) title("E. 2020 (Partisans)", size(small) nospan) plot1opts(color(blue*1.2) msize(small) msymbol(smcircle) lpattern(soild)) plot2opts(color(red*1.2) msize(small) msymbol(smcircle) lpattern(soild)) ylab(.2 (.1) 1, nogrid tlcolor(black) nogextend labs(small)) ylab(.2 (.1) 1, nogrid tlcolor(black)) xscale( lc(black)) yscale( lc(black)) addplot(scatter where1 COVIDCOVI_2020, ms(none) mlabel(pipe1) mlabpos(0) xlab(-2.9 (.4) 1.6, nogrid tlcolor(black) labs(small)) ylab(.2 (.1) 1, nogrid tlcolor(black)) legend(order(3 "Voted Democratic" 4 "Voted Republican") size(small) region(lcolor(white)) nospan)) legend(col(3) position(6)) scheme(s1mono) name(vc20_2)

melogit state_conf c.COVIDCOVI_2020##i.pres_2 b1.party3 i.votingmethod i.race4 female i.educ3 age date firm_num trifecta20 if sample == 1  & party3 == 2 [pw=norm_state_weight] || state_fips: 
su COVIDCOVI_2020, d
local min = r(min)
local max = r(max)
margins, at(COVIDCOVI_2020=(`r(min)' (0.1) `r(max)') pres_2=(0 1)) 
marginsplot, recastci(rarea) ciopts(color(gs10%40) lcolor(white)) yti("Predicted Probability of Confidence", size(small)) xti("Cost of Voting", size(small)) title("F. 2020 (Independents)", size(small) nospan) plot1opts(color(blue*1.2) msize(small) msymbol(smcircle) lpattern(soild)) plot2opts(color(red*1.2) msize(small) msymbol(smcircle) lpattern(soild)) ylab(.2 (.1) 1, nogrid tlcolor(black) nogextend labs(small)) ylab(.2 (.1) 1, nogrid tlcolor(black)) xscale( lc(black)) yscale( lc(black)) addplot(scatter where1 COVIDCOVI_2020, ms(none) mlabel(pipe1) mlabpos(0) xlab(-2.9 (.4) 1.6, nogrid tlcolor(black) labs(small)) ylab(.2 (.1) 1, nogrid tlcolor(black)) legend(order(3 "Voted Democratic" 4 "Voted Republican") size(small) region(lcolor(white)) nospan)) legend(col(3) position(6)) scheme(s1mono) name(vc20_3)

*** National ***
melogit national_conf c.COVIDCOVI_2020##b1.party3 i.votingmethod i.race4 female i.educ3 age date firm_num trifecta20 if sample == 1 [pw=norm_state_weight] || state_fips:
su COVIDCOVI_2020, d
local min = r(min)
local max = r(max)
margins, at(COVIDCOVI_2020=(`r(min)' (0.1) `r(max)') party3=(1 2 3)) 
marginsplot, recastci(rarea) ciopts(color(gs10%40) lcolor(white)) yti("Predicted Probability of Confidence", size(small)) xti("Cost of Voting", size(small)) title("D. 2020 (Integrity of Voting)", size(small) nospan) plot1opts(color(blue*1.2) msize(small) msymbol(smcircle) lpattern(soild)) plot2opts(color(purple*1.2) msize(small) msymbol(smcircle) lpattern(soild)) plot3opts(color(red*1.2) msize(small) msymbol(smcircle) lpattern(soild)) ylab(.2 (.1) 1, nogrid tlcolor(black) nogextend labs(small)) ylab(.2 (.1) 1, nogrid tlcolor(black)) xscale( lc(black)) yscale( lc(black)) addplot(scatter where1 COVIDCOVI_2020, ms(none) mlabel(pipe1) mlabpos(0) xlab(-2.9 (.4) 1.6, nogrid tlcolor(black) labs(small)) ylab(.2 (.1) 1, nogrid tlcolor(black)) legend(order(4 "Democrats" 5 "Independents" 6 "Republicans") size(small) region(lcolor(white)) nospan)) legend(col(3) position(6)) scheme(s1mono) name(n20_nsf)

*** Personal ***
melogit personal_conf c.COVIDCOVI_2020##b1.party3 i.votingmethod i.race4 female i.educ3 age date firm_num trifecta20 if sample == 1 [pw=norm_state_weight] || state_fips:
su COVIDCOVI_2020, d
local min = r(min)
local max = r(max)
margins, at(COVIDCOVI_2020=(`r(min)' (0.1) `r(max)') party3=(1 2 3)) 
marginsplot, recastci(rarea) ciopts(color(gs10%40) lcolor(white)) yti("Predicted Probability of Confidence", size(small)) xti("Cost of Voting", size(small)) title("D. 2020 (Integrity of Voting)", size(small) nospan) plot1opts(color(blue*1.2) msize(small) msymbol(smcircle) lpattern(soild)) plot2opts(color(purple*1.2) msize(small) msymbol(smcircle) lpattern(soild)) plot3opts(color(red*1.2) msize(small) msymbol(smcircle) lpattern(soild)) ylab(.2 (.1) 1, nogrid tlcolor(black) nogextend labs(small)) ylab(.2 (.1) 1, nogrid tlcolor(black)) xscale( lc(black)) yscale( lc(black)) addplot(scatter where1 COVIDCOVI_2020, ms(none) mlabel(pipe1) mlabpos(0) xlab(-2.9 (.4) 1.6, nogrid tlcolor(black) labs(small)) ylab(.2 (.1) 1, nogrid tlcolor(black)) legend(order(4 "Democrats" 5 "Independents" 6 "Republicans") size(small) region(lcolor(white)) nospan)) legend(col(3) position(6)) scheme(s1mono) name(p20_nsf)

*** Local ***
melogit county_conf c.COVIDCOVI_2020##b1.party3 i.votingmethod i.race4 female i.educ3 age date firm_num trifecta20 if sample == 1 [pw=norm_state_weight] || state_fips:
su COVIDCOVI_2020, d
local min = r(min)
local max = r(max)
margins, at(COVIDCOVI_2020=(`r(min)' (0.1) `r(max)') party3=(1 2 3)) 
marginsplot, recastci(rarea) ciopts(color(gs10%40) lcolor(white)) yti("Predicted Probability of Confidence", size(small)) xti("Cost of Voting", size(small)) title("D. 2020 (Integrity of Voting)", size(small) nospan) plot1opts(color(blue*1.2) msize(small) msymbol(smcircle) lpattern(soild)) plot2opts(color(purple*1.2) msize(small) msymbol(smcircle) lpattern(soild)) plot3opts(color(red*1.2) msize(small) msymbol(smcircle) lpattern(soild)) ylab(.2 (.1) 1, nogrid tlcolor(black) nogextend labs(small)) ylab(.2 (.1) 1, nogrid tlcolor(black)) xscale( lc(black)) yscale( lc(black)) addplot(scatter where1 COVIDCOVI_2020, ms(none) mlabel(pipe1) mlabpos(0) xlab(-2.9 (.4) 1.6, nogrid tlcolor(black) labs(small)) ylab(.2 (.1) 1, nogrid tlcolor(black)) legend(order(4 "Democrats" 5 "Independents" 6 "Republicans") size(small) region(lcolor(white)) nospan)) legend(col(3) position(6)) scheme(s1mono) name(l20_nsf)

